Understand what your

are talking about.

Go adaptive. Using a language-based approach, including knowledge graphs and NLU, we roll out AI chat and voice interfaces at scale.

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How does it work?

Better conversations begin with scraping, structuring and understanding data. The best conversations come from constantly improving that knowledge with real insights.

01

Scrape

02

Structure

03

Understand

04

Converse

01

02

03

04

Scrape

Structure

Understand

Converse

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Hyro automatically scrapes a variety of data sources such as websites, databases, APIs and beyond. When content updates, conversations update.

Seemingly unstructured data is then mapped to a knowledge graph (KG), made queryable by natural language.

Natural language understanding layers create a strong foundation for processing all types of phrasings, attributes and context.

Conversational AI interfaces, with text, touch and voice capabilities, are easily embedded across multiple channels.

Conversational Engine

Scrape

Require large caches of predefined intents, training sets, and playbooks to create limited conversational flows.

Scrape

Require large caches of predefined intents, training sets, and playbooks to create limited conversational flows.

Scrape

Require large caches of predefined intents,
training sets, and playbooks to create limited conversational flows.

Explore the industries that are putting adaptive communications to work.

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Discover why enterprises are switching from intent-based solutions to Hyro
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